March 26, 2025 • 43 mins
Explore how AI is transforming holistic health with Luca Cuccia, founder and CEO of Injoy. In this episode, Luca shares his personal journey of overcoming health challenges and his groundbreaking work in gut healthcare. Learn how AI is revolutionizing health data management, empowering practitioners with better insights, and freeing up more time for compassionate, patient-centered care.
Dive into the impact of AI in gut health, personalized wellness solutions, and how practitioners can integrate AI tools while maintaining the human touch in medicine. If you're curious about the future of holistic health and technology, this is a must-listen!
Check out Heallist.com for digital tools created just for holistic healers.
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Episode Transcript
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Yuli (00:04):
Welcome to the Healist Podcast, where we inspire and
guide healers through businessexpansion.
We give voice to incrediblyabundant healers to share their
stories.
We dive into the quantum fieldto unlock the energies of
conscious creation.
We also develop digital toolsto help you grow, which you can
(00:25):
find on healistcom.
I'm your host, Yuli, and I'mgrateful you chose to join this
space.
Now let's go deep.
Hello, dear friends, and welcometo another incredibly
insightful episode of theHealist Podcast.
I'm really, really thrilledabout having this conversation
about AI and holistic health,and I couldn't pick a better
(00:50):
guest.
Today we have the incrediblysmart Luca Cuccia, who is the
founder and CEO of Enjoy, ahealth tech startup
revolutionizing God Healthcarethrough AI and microbiome
science.
After battling cancer at age offive and later experiencing
(01:11):
inflammation issues himself, hemade it his mission to help
others facing similar challenges.
A McGill University graduate inpharmacology and therapeutics,
he was selected for theTechstars Montreal AI program
and named among Quickback's top25 emerging entrepreneurs.
(01:32):
Under his leadership, enjoy hasdeveloped an advanced
microbiome testing platform andgut chat and AI-powered health
assistant, and he's emerging asa thought leader in the gut
health space throughcollaborations with Olympic
athletes and documentary films.
I'm just so thrilled to haveLuca here with us and to shed
(01:54):
light on this very importanttopic that keeps everyone busy
these days and wondering aboutour future of humanity.
But we're here to talk aboutthe benefits or how actually AI
can help advance holistic health, and this is my intention for
this episode to really maybegive a new perspective to people
(02:17):
, especially to a lot ofholistic healers that might not
be familiar with AI or have somedifferent misconceptions about
it.
I love sharing stories howpeople actually use some of
those new tools to advancehumanity and our health.
So, luca, welcome to thepodcast.
Luca (02:37):
Thanks so much for having me Glee.
Yuli (02:39):
So I would like to dive just right in, right, as per
usual.
So I think it's such a bigtopic and I love to learn later
on about your journey and howyou got into it, because it
sounds just so fascinating.
But give us a quick overview ofAI and holistic health.
What does it mean exactly?
(03:00):
What is happening these days,and then maybe later, how can we
explore more about yourtechnology and how you're using
it for your incredible product?
Luca (03:10):
Beautiful, yeah, happy to.
So I think AI is one of thosethings that when I first got
into the space in 2019, it wasalready kind of a buzzword, but
this was the pre-large languagemodel period, right.
So when people thought of AI,they thought of AI in terms of
(03:30):
how do we use it to speed upprocesses that we already have?
How do we apply AI to big datasets to understand information
that might be hiding in there,less so what we have today,
where AI can be used to write anemail for someone at home, it
can be used to come up with aworkout plan, come up with the
(03:51):
diet plan, come up with allthese different things.
Ai was certainly in its infancy, and the way that we first
began to approach it was how dowe look at the microbiome, which
is this massive, massive,massive area of information, and
use it to essentially distilldown how someone is doing, are
(04:12):
they inflamed, are they sick,are they healthy?
So that's how we use AI, butwhat I would say more broadly in
terms of AI when it applies toholistic health, is that
practitioners today are becomingmore and more responsible for a
wide variety of areas of healthfor their clients and their
patients.
(04:32):
You know the past of havingspecialized care in areas of
exclusively gastroenterology,exclusively psychiatry and
mental health exclusively inother areas is starting to be
shifted, where now we havefunctional medicine
practitioners, holisticpractitioners, who are been
(04:53):
around for decades, but ofcourse we're now becoming a
bigger part of the patientjourney as people are beginning
to realize that my health cannotbe compartmentalized into one
area.
You know I can't fix one areaof how I'm feeling without
considering my mental health andmy diet simultaneously, for
example.
So that wider range ofexpertise now is where AI can be
(05:14):
a lot more supportive.
You as a practitioner aren'tgoing to be able to be sitting
with your patient or clientevery single day to understand
their eating habits, how they'refeeling, their day-to-day
fluctuations and symptoms and soon.
So the beauty of AI is thatwhen you do meet with your
clients, that understanding ofhow they've been doing in the
(05:37):
periods between your visits canbe understood from the get-go.
So you can understand whenyou're having that conversation
with this person, what has yourlife been like, as opposed to
just asking the question how areyou doing after not seeing
someone for 12 months, which iskind of how care typically works
now six to 12 months.
(05:57):
So it's a really beautifulsystem where we can make sure
knowledge isn't lost over longperiods, we can summarize it
into ways that are useful fordelivering care and we can have
these conversations with moreunderstanding, because
ultimately, technology bestserves as a complement to human
expertise At least that's how Isee it.
(06:19):
It's definitely not areplacement.
Ai is not replacing healthcareanytime soon, and that's with
respect to what we do.
We're heavily focused onenhancing care rather than
replacing human capability,because we see that as a way to
free up practitioners to focuson the deeper, more empathetic
interactions that are soimportant for healthcare
(06:39):
delivery.
So, while AI can effectivelyhandle the more routine
administrative tasks, likeanswering general questions,
checking up on people whilethey're away, patients
fundamentally trust and needhuman doctors for anything
involving a medical decision oreven emotional health decision,
(07:00):
because ultimately, care comesdown to two things safety and
trust, and I don't think of abetter group of practitioners to
do that, besides holistic careindividuals.
Yuli (07:12):
Now, I love that.
What you mentioned of this ideaof a holistic care right, and
looking at a person as a wholeand taking into account
different areas of their life,their body, into account
different areas of their life,their body and how much pressure
does it put on a practitionerto be able to take all that
(07:32):
information right, digest itpretty quickly into some sort of
I don't want to say diagnosis,but some sort of a conclusion,
right, and then provide care?
So that's just to break it downas a processing task.
Right, that's a big task andoften in holistic care we have a
(07:53):
little more time.
Usually a typical session lastsabout an hour.
In traditional care it'susually 15 minutes, right, so we
do have that hour, but it'sstill a pretty short amount of
time for a practitioner to beable to digest the information
and analyze it and come up withcare.
And I think this is such agreat point for AI to come in
(08:16):
and help solve Right.
Luca (08:19):
Yeah, and I think I think a really good example when it
comes to how this can be usefulis for something like diet
tracking.
Diet tracking is notoriouslydifficult, it's difficult for
people to do, nobody wants to doit, and then, even from the
practitioner side of things,it's notoriously difficult to
(08:40):
pull out those patterns of whatthe information is trying to
present to you.
So recognizing patterns issomething that humans can do
over the course of maybe one totwo days, but as soon as we get
to timescales that span weeks,that span months, that span
years, we start to lose the finedetails, and that's something
that AI is really good at.
(09:01):
So on top of that, we have thissubconscious issue where we
might forget or we might evenbecome accustomed to habits
which, over time, become our newregular.
So in my world, I get this alot, as you can imagine.
You know people who havecompletely forgotten that going
to the bathroom five times a dayis not normal, just because for
(09:23):
them it is.
You know, for them it's beenmonths and weeks that this has
been the normal for them.
So AI allows us to bring lightto those inconsistencies,
essentially show throughtracking and recognize these
issues and present them to youin ways that on a day-to-day
basis you might not recognize.
On a day-to-day basis you mightnot recognize.
(09:48):
Another area, for example, iswithin food intolerance tracking
.
Something like a dietaryintolerance if you're eating a
varied diet might not appearday-to-day, but overall you
might know something's off withwhat you're eating and how
you're feeling.
Typical example we get all thetime is that people say an apple
a day keeps the doctor away.
Right, but for someone who hascerebral bowel syndrome maybe
they have a sensitivity toFODMAP groups that apple could
(10:11):
be the reason that they'reexperiencing bloating and
abdominal pain and all thesedifferent things.
But most people would neverconsider it.
But by being able to apply an AIto what you're eating, the
symptoms you're experiencing anddrawing connections between the
two, we can highlight that thatapple is a problem for you and
it's something that you shouldtake a look at or try removing
(10:31):
from your diet.
So recognizing patterns is ahuge, huge, huge, huge area that
AI can be very useful.
Of course, consistent trackingis the first step, but again, ai
can be used to make that eveneasier.
Right, just taking a picture ofyour food as opposed to like
writing it down in a journal, orif you do write in a journal,
taking a picture of that journaland turning it into data that
(10:52):
the AI can then assess, becauseidentifying that issue whether
you're a dedicated practitioneror not is something that people
are looking for, and all of thisreally just becomes
contextualization for people whoare dealing with chronic issues
.
Really, trying to identify anysignatures in their health
before they become problematicis how we see it.
Yuli (11:14):
So let's double click a little bit on this idea of data
tracking, because I think that'swhere it kind of it all starts
and I still feel it's somethingthat is a bit disconnected from
our care, right?
I know a lot of people trackthat data on their own.
I'm a big some of you know I'ma big Oura Ring fan.
You know that's, yes, we all it.
(11:34):
Just, I think once you starttracking, you don't want to stop
because you're just getting somuch amazing useful information.
You know, I've tried differentmicrobiome tests that were also
like, really eye opening.
But I think a lot of thosetests these days, because
they're so accessibly availableto people, not necessarily when
(11:55):
I'm going and seeing a holisticpractitioner, I'm not
necessarily coming in with myOura Ring data, right?
So what do you see?
What are some of the challengesor some of the trends that you
(12:17):
see in this space in terms ofconnecting some of those
tracking devices or tests,whatever it is, connecting that
data basically and giving it topractitioners as a tool?
Luca (12:32):
Yeah, it's an excellent question.
I think a lot of the issuesthat we have is that our entire
medical system was not designedfor chronic care support.
You know, it was reallydesigned in the simplest fashion
of describing and whereaccidents, you know, broken
bones, things like this.
But as soon as issues arisewhere repeated care is necessary
(12:55):
, it becomes very difficult, andthat's why traditional care is,
you know, under so muchscrutiny and why holistic care
is so much more appreciated,because the whole point of it is
that time is given to theindividual when they come to see
you.
So, in terms of tracking andmaking that information relevant
for practitioners as a whole, Ithink a really important aspect
(13:18):
is connecting those pieces ofinformation let's say, you know
how you're sleeping, the amountof activity you're experiencing,
body temperature, all thesedifferent data points and
translating it into data that ismore familiar in the
practitioner world.
We do the same thing when itcomes to the microbiome, right?
I don't expect everypractitioner on the planet to
(13:40):
know specific bacteria and whatto do about them, but what we
try and focus on is making surethat we translate that data into
actions that they do understand.
So not looking at one area ofdata in isolation is definitely
critically important.
For example, you can't look atthe microbiome and ignore the
(14:00):
other areas of health, which is,I think, a downfall of a lot of
other companies that are outthere.
Instead, it should be looked atin the context of how you're
sleeping, what you're eating,how active you are, any symptoms
that you might be experiencing,because the truth is that's the
information that mostpractitioners will understand.
They understand symptoms.
They understand diet.
(14:22):
So whenever we track datawhether it be asking someone to
tell us how active they were theday before, how they slept,
what they might have ate,symptoms that we're experiencing
we always put it towardsstandardized metrics that any
practitioner will understand.
So these are more formallyknown as patient-reported
(14:45):
outcome measures.
They're kind of the surveysthat a practitioner might go
through with a patient when theyspeak with them.
But a lot of the data that wehave, like wearables, for
example, is not connected tothat.
So you go to your practitionerand you say, okay, look at my
Oura Ring score, here's myactivity score today, here's my
sleep score, and so on.
(15:06):
There's not much that can bedone with that currently, just
because it's not on a scale thatthey're familiar with, it's not
in a format that they'refamiliar with.
Something that we're reallyworking on now is how to
translate it to those scalesthat people are accustomed to
working with, just so that itcan be relevant within the
(15:26):
context of their care.
I think it's a big issue wherewe have all this amazing data
whether it be consistentlytracked through wearable,
passively tracked through stepson your phone but it doesn't
really get out of wellness and Ithink a lot of it is a
translation problem.
So that's really the big area,and how we make it applicable to
(15:47):
care is making sure thatinformation that's being tracked
whether it be in the wellnesssphere, wellness wearables
sphere or something else isbeing presented in a way that is
familiar, because you know youand I both know practitioners
are extremely busy.
I don't fault them for notwanting to learn new things, but
(16:09):
we can present them with newinformation, so long as it's in
a format they're accustomed toseeing.
Yuli (16:15):
Right, I think this is one of the issues that I'm seeing,
just as a user.
A lot of those apps andwearables, they have their own
scores right that all have adifferent calculation as well
and they're not alike.
Even just comparing twodifferent devices that measuring
sleep, right One person forexact same kind of you know
(16:35):
sleep increments and quality canget a much lower score than the
other one.
So there's still kind ofinconsistency because a lot of
those metrics, they'reproprietary metrics, right, that
just defined by these companies.
So even if we look at the score, which is the easier right
metric to translate and give tosomebody, even then I found
(16:56):
inconsistencies and my hope ismaybe with AI there will be some
standardization in the future.
Luca (17:02):
Someone will take up on that task of you know,
organizing all this data, which,yeah, yeah, yeah, I think data
organization is a big part of it, because before anything can be
translated into score, you haveto think of it needing to be
filtered to a degree.
We need to bring the data tothe same starting point.
(17:24):
So, kind of like what you weresaying, whether you have a
Fitbit, you have an Oura Ring,you have an 8-sleep mattress,
you have a Garmin watch,whatever it might be, they are
still tracking the same-ish datafor the most part how you're
sleeping, how you're active,body temperature changes.
But you're completely right,the output for that is a score.
(17:46):
It's a number, and almostalways we don't know how that
number is being calculated.
So an 80 on Aura might meansomething completely different
on Garmin, and that's not greatwhen it comes to healthcare,
where things need to bestandardized to a degree in
order to make comparisons andfor people to know what to do
next.
So that type of data cleaningis certainly an excellent AI
(18:07):
problem.
That type of data cleaning iscertainly an excellent AI
problem, and figuring out how toagain translate between tools
that are out there into formatsthat people are used to knowing,
or just helping people getaccess to the raw data you know
how long did you sleep and so on.
(18:31):
The only piece that I would addthere is that it's very
interesting to know sticking tothe sleep example example, how
many hours I slept the previousnight.
But what I think is morevaluable is to look at that over
a longitudinal period andunderstand how that sleep has
changed.
Because my normal could begetting seven hours a night and
that's perfectly fine for me Ifeel fresh, and all these things
, for For someone else it mightbe eight plus.
So the raw number only meanswhat it means to the individual
(18:54):
that it's coming from.
So what we really need tounderstand is any changes at
that person's level.
So if I'm always sleeping sevenhours and also I'm starting to
sleep five, that's a hugeproblem.
If I'm sleeping eight hours andnow I'm sleeping seven and a
half, maybe it's less of aproblem.
So we always like to try andfocus our analysis on the
individual person and highlightany changes from their kind of
(19:18):
normal baseline, as opposed tojust sticking everyone into a
rigid score where 100 is good,zero is bad.
We make it so that your 100 isunique to you to a degree Like.
(19:38):
The simplest example I couldthink of is that you know we
asked you how active you werethe day before.
For some person, a hundredcould mean running a marathon.
For someone, it can meanwalking across the room, right.
So it's really comes down toeffort and, again, making sure
that those scales are easy tounderstand and applicable to the
person they're being used for.
Yuli (19:54):
Absolutely, and just give a little context to our
listeners who might be new tothose wearables or the
personalized tests, all thosethings that we're really love
digging into the raw data.
This is part of my fun, justlike going to my Aura score and
clicking on the deep sleepversus REM sleep, because that's
(20:17):
where you really start gettinginsights and that's where you
can really adjust your lifestyleby just realizing, for example,
for me, strength training atnight, right before sleep,
dramatically multiplies my deepsleep score.
Don't ask me why, but my bodyjust goes into deep sleep right
(20:40):
after some not too vigorous butsome training.
So this was one example thatI've adjusted just by looking at
the raw data, because if I wasjust looking at the score I
would never kind of realize that.
But it is helpful and I can see, for even like holistic
practitioner just you know, yes,starting to use this data and
like double clicking and tryingto understand what is part of
(21:03):
the score and because if aperson, for example, is getting
like very low REM sleep, right,it's going to affect probably
their brain function.
We know that at this pointthere's a certain minimum that
we all need.
So how can you help themhighlight that An average person
would never know that unlessthey really research what REM
means and how does it impacttheir brain, so they can be that
(21:25):
bridge right that tells them.
And another example that Iwanted to give from my personal
just experiments, just, you know, doing the microbiome test, and
I want to talk more about yourtests and how that works because
it's really it's such afascinating topic but the one
I've done, what I did when Ireceived my scores and yes, it
was like the whole report ofmillion metrics and bacterias
(21:49):
and things like I don't evenunderstand what they are, but
the great insights where therewas actually actionable steps in
it, and the scores thathighlighted certain areas.
So, for example, in my case, ithighlighted that metabolic
health was, you know, got thelowest score.
So I knew, as an educatedpatient and I feel like we all
have to be these days right thisis also empowerment
(22:10):
conversation, not just forpractitioners but for anyone
that you know there's so muchdata you can access these days.
So once I saw that metabolichealth score, what I did?
I went to my holisticpractitioners and multiples
right that I'm using fordifferent areas and I gave them
this information and I said youknow, I come to you.
(22:30):
I've highlighted this issue ofmetabolic health.
What can you do for me?
And there was a combination ofherbs and, you know, vibrational
medicine that I'm taking.
Now that is totally changing itRight, but, but I think so.
So there's two sides of it One,empowering people to actually
use this data when they go toholistic practitioners, but also
for holistic practitioners tobe aware that there might be
(22:53):
data that they are not aware ofthat could really help their job
right.
Luca (23:00):
Yeah, I think that's huge.
Coming back to like uncoveringpatterns in your health that you
might not realize is a big one.
I've been wearing an Oura ringfor at least four years maybe
even longer than that and I cantell you I got it because I knew
I have trouble sleeping.
That's always been somethingthat I've had an issue with
growing up, so I wanted tounderstand again.
(23:22):
Similar to you, yuli, I'm avery data-driven person.
I wanted to see the objectiveside of things, outside of just
my mental how I'm thinking, I'mexperiencing things, and for me,
what was really cool is, in thesame way, that you were able to
identify okay, if I do weighttraining before sleep, I sleep
excellently.
For me, it was identifying thethings that are impacting my
(23:45):
sleep negatively, that areimpacting my sleep negatively.
So I think over the span ofseveral weeks, I started to look
at the data and look at the rawdata as the main source of
information, and very quickly Iwas able to tell if I eat like a
decently large meal withinthree hours of going to sleep.
My sleep is going to berestless.
(24:07):
I'm probably going to takelonger to fall asleep.
I won't go into deep or REMsleep as early as I typically
would, compared to if I, let'ssay, fast for at least four
hours before I go to sleepdepending on the size of the
meal, of course my sleep isdrastically, drastically,
drastically different.
Similar experience for alcohol.
(24:27):
I'm not a big drinker ingeneral, but I know, if I do
have a drink or two and then Ifall asleep within an hour of
that or two significantly lowerheart rate variability and so on
.
Even if I exercise during theday, the days where I'm able to
work out whether it be a hike orI go to the gym or something at
(24:48):
home heart rate is 20 to 30%higher in those evenings as
opposed to the days that I don't.
I think the tricky part thereis that Aura didn't tell me that
I still had to piece thingstogether, which is one of the
areas that I'm surprisedwearables just haven't improved
(25:09):
on.
I don't know if it's just aaccountability issue you know
they don't want to say somethingand be wrong about it, but for
us, you know we're heavilyfocused on that in our work.
That we do because we see theconfidence you can get from it.
Like for me, it's like I know.
You know, if I do these thingsI'm going to sleep pretty,
pretty well tonight, and thatsame type of feeling, that same
(25:33):
confidence in your body, is whatwe want people to experience
that are dealing with chronichealth issues.
Right, because I think there'sa lot of conversation around
suffering in silence, especiallywhen, let's say, it comes to
digestive health or gut healthissues, Because it's not like
you're missing a limb, it's notlike you're losing your hair.
(25:54):
These are things that people,for unjust and just reasons I
don't blame anyone for theirperspectives just might not
realize.
So the example of you coming todinner and not being able to
eat everything because you knowit's going to cause you issues,
and people just saying, oh,what's the big problem?
You know, just have it.
Especially around the holidays,that tends to be an issue for
(26:16):
people.
But being able to confidentlysay I can't eat this because I
know that it's going to impactmy symptoms I have the data to
show it, as well as my ownpersonal experiences that I can
show is really really powerfulfor people own personal
experiences that I can show isreally really powerful for
people, and we've had countlessof people who have taken our
tests and have used our app andsaid that the information that
(26:37):
we were able to uncover for themwas exactly what they needed to
then go see their practitionerwith confidence and advocate for
themselves at the base level.
So I think providing confidencefor people, feeling like they
understand what their body'strying to tell them, and getting
to the point where your data isbeing used to support your
(27:00):
health goals, is a really,really important level that we
want.
I think the main thing is tomake sure that you're keeping
your own thoughts in check asyou're looking at all this data,
because it can easily make yougo crazy at the same time if you
become too data obsessed.
So the one practice that Ialways recommend to everyone
that I know is that even beforeI look at my wearable data in
(27:23):
the morning because I stillreligiously, I check it every
single morning after all theseyears, for better or worse I
always try and think of how Iactually feel first, how do I
feel my rest was, how do I feellike I slept?
How refreshed do I feel?
Before I look at my aura score,because I think it's very easy
to get into the pattern of notreally thinking about it and
(27:45):
letting all of your feelings bedirected by those numbers, if I
wake up feeling great and thenmy sleep score is 60, I still
feel great, so I don't have toworry about it, but I think it's
because I took a moment toreflect on it before then.
So I think there's always abalance between data and being
data obsessed and then actuallymaking sure that it's supporting
(28:05):
your well-being as opposed tokind of being the bane of your
existence.
Yeah, absolutely.
Yuli (28:10):
Like mental health around the personal health data.
That would be the next frontier.
No, but you know what?
But it's funny that youmentioned that, because it
happened to me also that I wouldget like a super low scores and
I would wonder, but at the endthere was always something.
I would find out that it wassome lingering virus or
(28:31):
something that my body wasbattling at that point that I
just wasn't aware of, which is agreat thing.
Our bodies go through so much ona daily basis, so it was a good
thing.
But it also kind of forced meto respect that and say, okay,
I'm going to be more gentletoday because I don't know what
it is, but my body's goingthrough some stuff.
So but yes, it's a really goodpoint.
(28:54):
And I wanted to dig more intowhat you're doing with
microbiome, because it's such anew frontier, it's such an
incredible, totally underratedtopic that only now I feel like
people coming up with all thisevidence, how much impact that
it creates not just on ourphysical body but our emotional
(29:16):
bodies as well, and so it'sincredibly important research
and I feel like you're on areally on a front lines of
getting this all this amazinglike scientific research and all
this data from your users.
So I would like for you firstto explain what it actually does
in simple terms so ourlisteners can understand, and
(29:36):
then dig more into how utilizingall this incredible data to
help people.
Luca (29:43):
Yeah, a lot to get into there, and I think that the
easiest way to think about whatwe do is is by understanding our
philosophy right, because Ithink gut health has become a
topic that everyone has heard ofat this point, for for good
reasons, for bad reasons.
You know cleanses and so on.
You know taking the next bigtrend and wherever it takes you,
(30:05):
but I think the core of what wedo is just help people realize
that gut health is health.
It's not just your abdominalpain, it's not just your bloat,
it's your mental health, it'syour immune system, it's your
digestion, of course, but it'salso your skin, it's your weight
, it's everything, and it'ssomething that everybody can
(30:26):
benefit from.
You know, whether you'resomeone dealing with an active
inflammatory condition let's sayyou have Crohn's all the way to
someone who's at the peak oftheir health you know an Olympic
athlete just looking tooptimize.
Gut health has its place acrossthat entire you know, sick,
healthy spectrum, and I thinkthe problem that a lot of us
(30:49):
face today in the modern worldis that we're very disconnected
from our bodies, which I thinkis kind of what we're discussing
here, where wearables can helpus understand some of the
underpinnings of what's going onday to day.
But on top of that, we have somany external stressors, right,
we have processed foods thathave become the norm in the diet
(31:09):
for the high majority of people.
We have antibiotic overuse,which has its own problems.
We have environmental hazards,we have chronic stress and
because of that, our bodies aremissing out on a lot of the
natural elements that they need,contributing to a lot of the
widespread health issues that wesee today, especially in
chronic health.
And on top of this, becausewe're so busy, because we're
(31:34):
always running to the next thing, we don't take that time to
check in with our bodies.
So we've been on our ownjourneys, myself and Yuli as
well.
So being able to look into thatraw data is something that is
second nature to us, but I don'tput that expectation on
everyone.
And the sad part is that theresearch is showing that all
(31:54):
these innate systems in ourbodies are not isolated.
You know, they have far, farreaching impacts on things like
our mood and our health, morethan we ever once thought.
So that disconnection betweenus and our bodies is becoming
more and more important, andsome people are definitely aware
of it.
You know, that's kind of wherethe whole, I would say,
(32:15):
biohacking revolution is comingfrom, but the sad part is that a
lot of these people don'tnecessarily have the background
to act on it properly.
So we see people focused ontaking 30 different supplements
before they're even consideringthe fundamentals of their diet,
their sleep and their stress,which I think we all know is
(32:37):
that's going to have a muchlarger impact before the
supplements.
And if you don't address thosethings first, the supplements
can't have their effect.
So understanding the place forthose things is super important.
So for us, it really all comesdown to helping you understand
what your body's trying to tellyou.
The way I like to think of whatwe do is that we're essentially
just translators.
Your body has all theinformation it's trying to tell
(32:59):
you what it needs, but we're sodisconnected that we don't know
how to speak the languageanymore.
So what we really do is helppeople focus on those seven
hours that they're typicallyspending in the bathroom on a
weekly basis and turn that intoconcrete, powerful health
insights using artificialintelligence, using microbiome
(33:21):
testing, using smart sensors,because there's around 60% of
people, especially adults, whoare struggling with gut health
issues and health issues ingeneral, and they're
experiencing symptoms butthey're not able to make the
leap of turn it into?
What do I do next so that guthealth optimization is something
that we're really focused on,so that we can make gut health
(33:44):
and health itself as natural asyour daily routine, essentially?
Yuli (33:50):
So, and the product itself is essentially a test right.
Luca (33:55):
Yeah, the product itself is a combination of three things
it's a at-home microbiome test,it's a app and it's a bathroom
sensor.
So the bathroom sensor isreally about habit formation.
Essentially, it uses Bluetoothto recognize when you go to the
bathroom with your phone.
We'll send you a reminder tocheck in with our app, and it's
(34:17):
also able to passively track howlong you're in the bathroom,
how frequently you're going,which is important to get to
know.
And in the app you can do a lotof things.
You can tell us about thesymptoms you're experiencing,
your diet, your mental health.
You can track basically all theimportant areas of your
well-being.
But on top of that, it's also atrustworthy informational
(34:38):
resource.
So we have a tool called GutChat, similar to conversational
chat that you might experiencein other apps, but the unique
thing about ours is that it'snot connected to the internet
and it's actually trained onhundreds of thousands of
peer-reviewed academicliterature.
(34:58):
So when you ask a question, youcan be very confident that the
information is coming from aplace of trust, something that's
been reviewed by otherscientists and so on, and we
always make sure to cite thatinformation so you can see the
exact resources that it's comingfrom.
On top of that, we make itreally easy for you to dig into
topics.
(35:19):
So if you ask a question aftera response, we'll give you some
follow-up questions you can ask.
You can just keep diving deeperinto topics and again get that
confidence in areas of yourhealth that either might be
uncomfortable to discuss withother people or you've just
never known what to trust,Because when you Google it you
just kind of see a slew ofinformation everywhere.
Yuli (35:39):
So education and tracking are two big things I just pause
you there because I think it's avery important topic that you
just touched on with the ai chatfeature, and I just want to
make sure that our listenersfully understood that, because
you kind of isolate this dataand you control the sources of
(36:00):
this data.
It's a very different and, justyou know, asking Chad GBT what
is this gut symptom that I'mhaving, right?
So you created your own kind ofthis trusted source that, yes,
people can converse and maybesense more privacy than sharing
it with, even with theirpractitioner, right but at the
(36:21):
same time, they also can trustthat the data and advice they
get comes from trusted sources,which I think is another big
issue.
Kind of look back to our AIconversation.
Another big issue that we'reseeing is this mistrust of data,
or data that is oftenmisleading or creating
misinformation.
So I just love that idea and Iwanted to emphasize and maybe,
(36:45):
like educate right our audienceon that.
It is one of the use cases ofAI these days and this is
something that allows you tohave that again trusted source
and valuable information thatyou know, if you asked an
average practitioner to rememberall this incredible research
(37:07):
right that you're able to storein this one kind of library of
content that would be justimpossible for an individual.
But again, with AI you're ableto access like countless of
research and have that in yourfingertips.
So I just wanted to emphasizethat, because it's funny how we
talked today about some of thosethings that are so obvious,
(37:28):
right, but like just a few yearsago, you could never imagine
doing that, right.
Luca (37:34):
No, you couldn't, and the information comes out so quickly
that even if you tried, youwouldn't be able to keep up
right.
So us being able to pull theinformation from the literature
as it's coming out and distillit into a way that you can ask
questions about very easily is ahuge, huge, huge benefit to
practitioners, not only fortheir own knowledge but also for
(37:56):
their patients, right whenthey're away from the care.
They're able to ask questions,to get responses from databases
they can trust, which is super,super important, because for us,
transparency in data is areally big item that we talk
about a lot LLMs, these chat,gpts and so on that are out
(38:16):
there.
When you ask a question, youhave no idea where it pulled
that information from, and mostof these tools are also not
connected to the internet mostof the time, but in a way that
doesn't benefit them, becausethat means a lot of their
information is outdated andbecause they have such a
widespread amount of information, including a download of the
entire internet, they don'tnecessarily know.
(38:39):
You know, is this random blogcorrect, or is it something that
is potentially giving mecompletely false information?
We don't have that problembecause all of our resources are
peer-reviewed literature.
So we're able to pull from theresources, we're able to see
papers that are saying similarthings.
Papers that have lessreproducibility can be ignored,
(39:01):
for example, and we always,always cite information.
We will show you the exactpaper that it came from so that
you can go look into it yourselfdeeper and again feel that
confidence of the informationthat's there.
So being able to one-up youreducation is something that's
super important, and then thenext layer on top of that is
(39:23):
receiving those responses,receiving those information in a
way that's easilyunderstandable, because, coming
from my science background, oneof the things that I never
understood is that why academicliterature is so difficult to
read.
It's written extremely dry,there's a lot of technical
jargon, and it makes it so thatvery few people can get value
(39:49):
from it.
And that's why so much of thegreat information and the great
resource that's happening staysin the academic sphere, because
people just don't know what it'ssaying.
And that's not.
You know, even if you're aprofessor, you go from one
department to the next.
It might be like speakinganother language.
So for us, it's not just beingable to get access to
information, but also in aformat that you can easily
(40:10):
understand, and, on top of that,with contextualization of your
individual needs.
If you ask about a specificbacteria, a specific probiotic,
specific diet, we can give you aresponse from literature about
all the information you need toknow, but also how it's
applicable to you, because wealso know about your diet, we
(40:32):
know about your symptoms.
We could say this looks like itcould be useful for you because
of what you're eating, becausethe symptoms you're experiencing
, and just become so much morerelevant as a result of that.
So personalization is anotherkey area that AI can be
supportive of.
Yuli (40:48):
Amazing.
Well, thank you for thisincredible overview and I can
believe it's been.
We're running out of time.
There's so many more questionsthat I want to ask you, but as
to kind of wrap things up forbecause I think we gave a lot of
information to people, what canpractitioners do today?
What are kind of the mostimmediate things that they can
(41:10):
start incorporate into theirpractice whether it's data, ai,
different tools just to get moreaccess to this valuable
information and enhance theirservices?
Luca (41:22):
this valuable information and enhance their services.
Yeah, I think one of the mostimportant things that people can
do is use AI as something tosupport education.
I think is a really, really bigone.
So being able to keep up todate on information.
There's several evennewsletters out there that are
constantly distilling all theinformation from different areas
(41:42):
of health, that are constantlydistilling all the information
from different areas of healththat are super relevant for
people to keep up with.
Down to just managing yourday-to-day practice right.
How do you support peoplebetter when they're not directly
in front of you?
Ai is going to be the best wayto do that.
Obviously, I'm biased.
I'm going to say my products isthe best thing to do that to
give people confidence in theirhealth outside of direct care.
(42:04):
But there are many differentoptions that go beyond simply
journaling in your phone as thebest option and certainly better
than just Googling it to seewhat information might be there.
So I think practitioners shoulddefinitely take the leap in
understanding that AI could be acomplement to their care.
I've been in this space forfive years.
I can tell you we are nowherenear replacement, nor do I think
(42:26):
it's ever possible, justbecause of the human touch, care
it requires.
And so, yeah, just making AIpart of your practice and the
way that you deliver to people.
Yuli (42:37):
And considering some of those incredible products, like
your test incorporating into it.
We're seeing a lot ofpractitioners also creating
partnerships with or just usingit on their own by recommending
some of those tests and tools totheir clients because it gives
them a lot more data, right,Certainly, certainly.
Well, thank you so much forsharing this wall of knowledge.
(42:59):
We didn't get to talk aboutyour personal story because we
ran out of time, so we mighthave to do a part two because
that sounds fascinating and somuch you've overcome to get here
and help so many other people.
So really appreciate yourmission, your journey, sharing
all of this incredible insightsfor Alyssa.
Thank you so much, Luca.
Luca (43:20):
My pleasure.
Thanks so much, Luca, mypleasure.
Thanks so much Julie.
Welcome to the Healist Podcast, where we inspire and
guide healers through businessexpansion.
We give voice to incrediblyabundant healers to share their
stories.
We dive into the quantum fieldto unlock the energies of
conscious creation.
We also develop digital toolsto help you grow, which you can
(00:25):
find on healistcom.
I'm your host, Yuli, and I'mgrateful you chose to join this
space.
Now let's go deep.
Hello, dear friends, and welcometo another incredibly
insightful episode of theHealist Podcast.
I'm really, really thrilledabout having this conversation
about AI and holistic health,and I couldn't pick a better
(00:50):
guest.
Today we have the incrediblysmart Luca Cuccia, who is the
founder and CEO of Enjoy, ahealth tech startup
revolutionizing God Healthcarethrough AI and microbiome
science.
After battling cancer at age offive and later experiencing
(01:11):
inflammation issues himself, hemade it his mission to help
others facing similar challenges.
A McGill University graduate inpharmacology and therapeutics,
he was selected for theTechstars Montreal AI program
and named among Quickback's top25 emerging entrepreneurs.
(01:32):
Under his leadership, enjoy hasdeveloped an advanced
microbiome testing platform andgut chat and AI-powered health
assistant, and he's emerging asa thought leader in the gut
health space throughcollaborations with Olympic
athletes and documentary films.
I'm just so thrilled to haveLuca here with us and to shed
(01:54):
light on this very importanttopic that keeps everyone busy
these days and wondering aboutour future of humanity.
But we're here to talk aboutthe benefits or how actually AI
can help advance holistic health, and this is my intention for
this episode to really maybegive a new perspective to people
(02:17):
, especially to a lot ofholistic healers that might not
be familiar with AI or have somedifferent misconceptions about
it.
I love sharing stories howpeople actually use some of
those new tools to advancehumanity and our health.
So, luca, welcome to thepodcast.
Luca (02:37):
Thanks so much for having me Glee.
Yuli (02:39):
So I would like to dive just right in, right, as per
usual.
So I think it's such a bigtopic and I love to learn later
on about your journey and howyou got into it, because it
sounds just so fascinating.
But give us a quick overview ofAI and holistic health.
What does it mean exactly?
(03:00):
What is happening these days,and then maybe later, how can we
explore more about yourtechnology and how you're using
it for your incredible product?
Luca (03:10):
Beautiful, yeah, happy to.
So I think AI is one of thosethings that when I first got
into the space in 2019, it wasalready kind of a buzzword, but
this was the pre-large languagemodel period, right.
So when people thought of AI,they thought of AI in terms of
(03:30):
how do we use it to speed upprocesses that we already have?
How do we apply AI to big datasets to understand information
that might be hiding in there,less so what we have today,
where AI can be used to write anemail for someone at home, it
can be used to come up with aworkout plan, come up with the
(03:51):
diet plan, come up with allthese different things.
Ai was certainly in its infancy, and the way that we first
began to approach it was how dowe look at the microbiome, which
is this massive, massive,massive area of information, and
use it to essentially distilldown how someone is doing, are
(04:12):
they inflamed, are they sick,are they healthy?
So that's how we use AI, butwhat I would say more broadly in
terms of AI when it applies toholistic health, is that
practitioners today are becomingmore and more responsible for a
wide variety of areas of healthfor their clients and their
patients.
(04:32):
You know the past of havingspecialized care in areas of
exclusively gastroenterology,exclusively psychiatry and
mental health exclusively inother areas is starting to be
shifted, where now we havefunctional medicine
practitioners, holisticpractitioners, who are been
(04:53):
around for decades, but ofcourse we're now becoming a
bigger part of the patientjourney as people are beginning
to realize that my health cannotbe compartmentalized into one
area.
You know I can't fix one areaof how I'm feeling without
considering my mental health andmy diet simultaneously, for
example.
So that wider range ofexpertise now is where AI can be
(05:14):
a lot more supportive.
You as a practitioner aren'tgoing to be able to be sitting
with your patient or clientevery single day to understand
their eating habits, how they'refeeling, their day-to-day
fluctuations and symptoms and soon.
So the beauty of AI is thatwhen you do meet with your
clients, that understanding ofhow they've been doing in the
(05:37):
periods between your visits canbe understood from the get-go.
So you can understand whenyou're having that conversation
with this person, what has yourlife been like, as opposed to
just asking the question how areyou doing after not seeing
someone for 12 months, which iskind of how care typically works
now six to 12 months.
(05:57):
So it's a really beautifulsystem where we can make sure
knowledge isn't lost over longperiods, we can summarize it
into ways that are useful fordelivering care and we can have
these conversations with moreunderstanding, because
ultimately, technology bestserves as a complement to human
expertise At least that's how Isee it.
(06:19):
It's definitely not areplacement.
Ai is not replacing healthcareanytime soon, and that's with
respect to what we do.
We're heavily focused onenhancing care rather than
replacing human capability,because we see that as a way to
free up practitioners to focuson the deeper, more empathetic
interactions that are soimportant for healthcare
(06:39):
delivery.
So, while AI can effectivelyhandle the more routine
administrative tasks, likeanswering general questions,
checking up on people whilethey're away, patients
fundamentally trust and needhuman doctors for anything
involving a medical decision oreven emotional health decision,
(07:00):
because ultimately, care comesdown to two things safety and
trust, and I don't think of abetter group of practitioners to
do that, besides holistic careindividuals.
Yuli (07:12):
Now, I love that.
What you mentioned of this ideaof a holistic care right, and
looking at a person as a wholeand taking into account
different areas of their life,their body, into account
different areas of their life,their body and how much pressure
does it put on a practitionerto be able to take all that
(07:32):
information right, digest itpretty quickly into some sort of
I don't want to say diagnosis,but some sort of a conclusion,
right, and then provide care?
So that's just to break it downas a processing task.
Right, that's a big task andoften in holistic care we have a
(07:53):
little more time.
Usually a typical session lastsabout an hour.
In traditional care it'susually 15 minutes, right, so we
do have that hour, but it'sstill a pretty short amount of
time for a practitioner to beable to digest the information
and analyze it and come up withcare.
And I think this is such agreat point for AI to come in
(08:16):
and help solve Right.
Luca (08:19):
Yeah, and I think I think a really good example when it
comes to how this can be usefulis for something like diet
tracking.
Diet tracking is notoriouslydifficult, it's difficult for
people to do, nobody wants to doit, and then, even from the
practitioner side of things,it's notoriously difficult to
(08:40):
pull out those patterns of whatthe information is trying to
present to you.
So recognizing patterns issomething that humans can do
over the course of maybe one totwo days, but as soon as we get
to timescales that span weeks,that span months, that span
years, we start to lose the finedetails, and that's something
that AI is really good at.
(09:01):
So on top of that, we have thissubconscious issue where we
might forget or we might evenbecome accustomed to habits
which, over time, become our newregular.
So in my world, I get this alot, as you can imagine.
You know people who havecompletely forgotten that going
to the bathroom five times a dayis not normal, just because for
(09:23):
them it is.
You know, for them it's beenmonths and weeks that this has
been the normal for them.
So AI allows us to bring lightto those inconsistencies,
essentially show throughtracking and recognize these
issues and present them to youin ways that on a day-to-day
basis you might not recognize.
On a day-to-day basis you mightnot recognize.
(09:48):
Another area, for example, iswithin food intolerance tracking
.
Something like a dietaryintolerance if you're eating a
varied diet might not appearday-to-day, but overall you
might know something's off withwhat you're eating and how
you're feeling.
Typical example we get all thetime is that people say an apple
a day keeps the doctor away.
Right, but for someone who hascerebral bowel syndrome maybe
they have a sensitivity toFODMAP groups that apple could
(10:11):
be the reason that they'reexperiencing bloating and
abdominal pain and all thesedifferent things.
But most people would neverconsider it.
But by being able to apply an AIto what you're eating, the
symptoms you're experiencing anddrawing connections between the
two, we can highlight that thatapple is a problem for you and
it's something that you shouldtake a look at or try removing
(10:31):
from your diet.
So recognizing patterns is ahuge, huge, huge, huge area that
AI can be very useful.
Of course, consistent trackingis the first step, but again, ai
can be used to make that eveneasier.
Right, just taking a picture ofyour food as opposed to like
writing it down in a journal, orif you do write in a journal,
taking a picture of that journaland turning it into data that
(10:52):
the AI can then assess, becauseidentifying that issue whether
you're a dedicated practitioneror not is something that people
are looking for, and all of thisreally just becomes
contextualization for people whoare dealing with chronic issues
.
Really, trying to identify anysignatures in their health
before they become problematicis how we see it.
Yuli (11:14):
So let's double click a little bit on this idea of data
tracking, because I think that'swhere it kind of it all starts
and I still feel it's somethingthat is a bit disconnected from
our care, right?
I know a lot of people trackthat data on their own.
I'm a big some of you know I'ma big Oura Ring fan.
You know that's, yes, we all it.
(11:34):
Just, I think once you starttracking, you don't want to stop
because you're just getting somuch amazing useful information.
You know, I've tried differentmicrobiome tests that were also
like, really eye opening.
But I think a lot of thosetests these days, because
they're so accessibly availableto people, not necessarily when
(11:55):
I'm going and seeing a holisticpractitioner, I'm not
necessarily coming in with myOura Ring data, right?
So what do you see?
What are some of the challengesor some of the trends that you
(12:17):
see in this space in terms ofconnecting some of those
tracking devices or tests,whatever it is, connecting that
data basically and giving it topractitioners as a tool?
Luca (12:32):
Yeah, it's an excellent question.
I think a lot of the issuesthat we have is that our entire
medical system was not designedfor chronic care support.
You know, it was reallydesigned in the simplest fashion
of describing and whereaccidents, you know, broken
bones, things like this.
But as soon as issues arisewhere repeated care is necessary
(12:55):
, it becomes very difficult, andthat's why traditional care is,
you know, under so muchscrutiny and why holistic care
is so much more appreciated,because the whole point of it is
that time is given to theindividual when they come to see
you.
So, in terms of tracking andmaking that information relevant
for practitioners as a whole, Ithink a really important aspect
(13:18):
is connecting those pieces ofinformation let's say, you know
how you're sleeping, the amountof activity you're experiencing,
body temperature, all thesedifferent data points and
translating it into data that ismore familiar in the
practitioner world.
We do the same thing when itcomes to the microbiome, right?
I don't expect everypractitioner on the planet to
(13:40):
know specific bacteria and whatto do about them, but what we
try and focus on is making surethat we translate that data into
actions that they do understand.
So not looking at one area ofdata in isolation is definitely
critically important.
For example, you can't look atthe microbiome and ignore the
(14:00):
other areas of health, which is,I think, a downfall of a lot of
other companies that are outthere.
Instead, it should be looked atin the context of how you're
sleeping, what you're eating,how active you are, any symptoms
that you might be experiencing,because the truth is that's the
information that mostpractitioners will understand.
They understand symptoms.
They understand diet.
(14:22):
So whenever we track datawhether it be asking someone to
tell us how active they were theday before, how they slept,
what they might have ate,symptoms that we're experiencing
we always put it towardsstandardized metrics that any
practitioner will understand.
So these are more formallyknown as patient-reported
(14:45):
outcome measures.
They're kind of the surveysthat a practitioner might go
through with a patient when theyspeak with them.
But a lot of the data that wehave, like wearables, for
example, is not connected tothat.
So you go to your practitionerand you say, okay, look at my
Oura Ring score, here's myactivity score today, here's my
sleep score, and so on.
(15:06):
There's not much that can bedone with that currently, just
because it's not on a scale thatthey're familiar with, it's not
in a format that they'refamiliar with.
Something that we're reallyworking on now is how to
translate it to those scalesthat people are accustomed to
working with, just so that itcan be relevant within the
(15:26):
context of their care.
I think it's a big issue wherewe have all this amazing data
whether it be consistentlytracked through wearable,
passively tracked through stepson your phone but it doesn't
really get out of wellness and Ithink a lot of it is a
translation problem.
So that's really the big area,and how we make it applicable to
(15:47):
care is making sure thatinformation that's being tracked
whether it be in the wellnesssphere, wellness wearables
sphere or something else isbeing presented in a way that is
familiar, because you know youand I both know practitioners
are extremely busy.
I don't fault them for notwanting to learn new things, but
(16:09):
we can present them with newinformation, so long as it's in
a format they're accustomed toseeing.
Yuli (16:15):
Right, I think this is one of the issues that I'm seeing,
just as a user.
A lot of those apps andwearables, they have their own
scores right that all have adifferent calculation as well
and they're not alike.
Even just comparing twodifferent devices that measuring
sleep, right One person forexact same kind of you know
(16:35):
sleep increments and quality canget a much lower score than the
other one.
So there's still kind ofinconsistency because a lot of
those metrics, they'reproprietary metrics, right, that
just defined by these companies.
So even if we look at the score, which is the easier right
metric to translate and give tosomebody, even then I found
(16:56):
inconsistencies and my hope ismaybe with AI there will be some
standardization in the future.
Luca (17:02):
Someone will take up on that task of you know,
organizing all this data, which,yeah, yeah, yeah, I think data
organization is a big part of it, because before anything can be
translated into score, you haveto think of it needing to be
filtered to a degree.
We need to bring the data tothe same starting point.
(17:24):
So, kind of like what you weresaying, whether you have a
Fitbit, you have an Oura Ring,you have an 8-sleep mattress,
you have a Garmin watch,whatever it might be, they are
still tracking the same-ish datafor the most part how you're
sleeping, how you're active,body temperature changes.
But you're completely right,the output for that is a score.
(17:46):
It's a number, and almostalways we don't know how that
number is being calculated.
So an 80 on Aura might meansomething completely different
on Garmin, and that's not greatwhen it comes to healthcare,
where things need to bestandardized to a degree in
order to make comparisons andfor people to know what to do
next.
So that type of data cleaningis certainly an excellent AI
(18:07):
problem.
That type of data cleaning iscertainly an excellent AI
problem, and figuring out how toagain translate between tools
that are out there into formatsthat people are used to knowing,
or just helping people getaccess to the raw data you know
how long did you sleep and so on.
(18:31):
The only piece that I would addthere is that it's very
interesting to know sticking tothe sleep example example, how
many hours I slept the previousnight.
But what I think is morevaluable is to look at that over
a longitudinal period andunderstand how that sleep has
changed.
Because my normal could begetting seven hours a night and
that's perfectly fine for me Ifeel fresh, and all these things
, for For someone else it mightbe eight plus.
So the raw number only meanswhat it means to the individual
(18:54):
that it's coming from.
So what we really need tounderstand is any changes at
that person's level.
So if I'm always sleeping sevenhours and also I'm starting to
sleep five, that's a hugeproblem.
If I'm sleeping eight hours andnow I'm sleeping seven and a
half, maybe it's less of aproblem.
So we always like to try andfocus our analysis on the
individual person and highlightany changes from their kind of
(19:18):
normal baseline, as opposed tojust sticking everyone into a
rigid score where 100 is good,zero is bad.
We make it so that your 100 isunique to you to a degree Like.
(19:38):
The simplest example I couldthink of is that you know we
asked you how active you werethe day before.
For some person, a hundredcould mean running a marathon.
For someone, it can meanwalking across the room, right.
So it's really comes down toeffort and, again, making sure
that those scales are easy tounderstand and applicable to the
person they're being used for.
Yuli (19:54):
Absolutely, and just give a little context to our
listeners who might be new tothose wearables or the
personalized tests, all thosethings that we're really love
digging into the raw data.
This is part of my fun, justlike going to my Aura score and
clicking on the deep sleepversus REM sleep, because that's
(20:17):
where you really start gettinginsights and that's where you
can really adjust your lifestyleby just realizing, for example,
for me, strength training atnight, right before sleep,
dramatically multiplies my deepsleep score.
Don't ask me why, but my bodyjust goes into deep sleep right
(20:40):
after some not too vigorous butsome training.
So this was one example thatI've adjusted just by looking at
the raw data, because if I wasjust looking at the score I
would never kind of realize that.
But it is helpful and I can see, for even like holistic
practitioner just you know, yes,starting to use this data and
like double clicking and tryingto understand what is part of
(21:03):
the score and because if aperson, for example, is getting
like very low REM sleep, right,it's going to affect probably
their brain function.
We know that at this pointthere's a certain minimum that
we all need.
So how can you help themhighlight that An average person
would never know that unlessthey really research what REM
means and how does it impacttheir brain, so they can be that
(21:25):
bridge right that tells them.
And another example that Iwanted to give from my personal
just experiments, just, you know, doing the microbiome test, and
I want to talk more about yourtests and how that works because
it's really it's such afascinating topic but the one
I've done, what I did when Ireceived my scores and yes, it
was like the whole report ofmillion metrics and bacterias
(21:49):
and things like I don't evenunderstand what they are, but
the great insights where therewas actually actionable steps in
it, and the scores thathighlighted certain areas.
So, for example, in my case, ithighlighted that metabolic
health was, you know, got thelowest score.
So I knew, as an educatedpatient and I feel like we all
have to be these days right thisis also empowerment
(22:10):
conversation, not just forpractitioners but for anyone
that you know there's so muchdata you can access these days.
So once I saw that metabolichealth score, what I did?
I went to my holisticpractitioners and multiples
right that I'm using fordifferent areas and I gave them
this information and I said youknow, I come to you.
(22:30):
I've highlighted this issue ofmetabolic health.
What can you do for me?
And there was a combination ofherbs and, you know, vibrational
medicine that I'm taking.
Now that is totally changing itRight, but, but I think so.
So there's two sides of it One,empowering people to actually
use this data when they go toholistic practitioners, but also
for holistic practitioners tobe aware that there might be
(22:53):
data that they are not aware ofthat could really help their job
right.
Luca (23:00):
Yeah, I think that's huge.
Coming back to like uncoveringpatterns in your health that you
might not realize is a big one.
I've been wearing an Oura ringfor at least four years maybe
even longer than that and I cantell you I got it because I knew
I have trouble sleeping.
That's always been somethingthat I've had an issue with
growing up, so I wanted tounderstand again.
(23:22):
Similar to you, yuli, I'm avery data-driven person.
I wanted to see the objectiveside of things, outside of just
my mental how I'm thinking, I'mexperiencing things, and for me,
what was really cool is, in thesame way, that you were able to
identify okay, if I do weighttraining before sleep, I sleep
excellently.
For me, it was identifying thethings that are impacting my
(23:45):
sleep negatively, that areimpacting my sleep negatively.
So I think over the span ofseveral weeks, I started to look
at the data and look at the rawdata as the main source of
information, and very quickly Iwas able to tell if I eat like a
decently large meal withinthree hours of going to sleep.
My sleep is going to berestless.
(24:07):
I'm probably going to takelonger to fall asleep.
I won't go into deep or REMsleep as early as I typically
would, compared to if I, let'ssay, fast for at least four
hours before I go to sleepdepending on the size of the
meal, of course my sleep isdrastically, drastically,
drastically different.
Similar experience for alcohol.
(24:27):
I'm not a big drinker ingeneral, but I know, if I do
have a drink or two and then Ifall asleep within an hour of
that or two significantly lowerheart rate variability and so on
.
Even if I exercise during theday, the days where I'm able to
work out whether it be a hike orI go to the gym or something at
(24:48):
home heart rate is 20 to 30%higher in those evenings as
opposed to the days that I don't.
I think the tricky part thereis that Aura didn't tell me that
I still had to piece thingstogether, which is one of the
areas that I'm surprisedwearables just haven't improved
(25:09):
on.
I don't know if it's just aaccountability issue you know
they don't want to say somethingand be wrong about it, but for
us, you know we're heavilyfocused on that in our work.
That we do because we see theconfidence you can get from it.
Like for me, it's like I know.
You know, if I do these thingsI'm going to sleep pretty,
pretty well tonight, and thatsame type of feeling, that same
(25:33):
confidence in your body, is whatwe want people to experience
that are dealing with chronichealth issues.
Right, because I think there'sa lot of conversation around
suffering in silence, especiallywhen, let's say, it comes to
digestive health or gut healthissues, Because it's not like
you're missing a limb, it's notlike you're losing your hair.
(25:54):
These are things that people,for unjust and just reasons I
don't blame anyone for theirperspectives just might not
realize.
So the example of you coming todinner and not being able to
eat everything because you knowit's going to cause you issues,
and people just saying, oh,what's the big problem?
You know, just have it.
Especially around the holidays,that tends to be an issue for
(26:16):
people.
But being able to confidentlysay I can't eat this because I
know that it's going to impactmy symptoms I have the data to
show it, as well as my ownpersonal experiences that I can
show is really really powerfulfor people own personal
experiences that I can show isreally really powerful for
people, and we've had countlessof people who have taken our
tests and have used our app andsaid that the information that
(26:37):
we were able to uncover for themwas exactly what they needed to
then go see their practitionerwith confidence and advocate for
themselves at the base level.
So I think providing confidencefor people, feeling like they
understand what their body'strying to tell them, and getting
to the point where your data isbeing used to support your
(27:00):
health goals, is a really,really important level that we
want.
I think the main thing is tomake sure that you're keeping
your own thoughts in check asyou're looking at all this data,
because it can easily make yougo crazy at the same time if you
become too data obsessed.
So the one practice that Ialways recommend to everyone
that I know is that even beforeI look at my wearable data in
(27:23):
the morning because I stillreligiously, I check it every
single morning after all theseyears, for better or worse I
always try and think of how Iactually feel first, how do I
feel my rest was, how do I feellike I slept?
How refreshed do I feel?
Before I look at my aura score,because I think it's very easy
to get into the pattern of notreally thinking about it and
(27:45):
letting all of your feelings bedirected by those numbers, if I
wake up feeling great and thenmy sleep score is 60, I still
feel great, so I don't have toworry about it, but I think it's
because I took a moment toreflect on it before then.
So I think there's always abalance between data and being
data obsessed and then actuallymaking sure that it's supporting
(28:05):
your well-being as opposed tokind of being the bane of your
existence.
Yeah, absolutely.
Yuli (28:10):
Like mental health around the personal health data.
That would be the next frontier.
No, but you know what?
But it's funny that youmentioned that, because it
happened to me also that I wouldget like a super low scores and
I would wonder, but at the endthere was always something.
I would find out that it wassome lingering virus or
(28:31):
something that my body wasbattling at that point that I
just wasn't aware of, which is agreat thing.
Our bodies go through so much ona daily basis, so it was a good
thing.
But it also kind of forced meto respect that and say, okay,
I'm going to be more gentletoday because I don't know what
it is, but my body's goingthrough some stuff.
So but yes, it's a really goodpoint.
(28:54):
And I wanted to dig more intowhat you're doing with
microbiome, because it's such anew frontier, it's such an
incredible, totally underratedtopic that only now I feel like
people coming up with all thisevidence, how much impact that
it creates not just on ourphysical body but our emotional
(29:16):
bodies as well, and so it'sincredibly important research
and I feel like you're on areally on a front lines of
getting this all this amazinglike scientific research and all
this data from your users.
So I would like for you firstto explain what it actually does
in simple terms so ourlisteners can understand, and
(29:36):
then dig more into how utilizingall this incredible data to
help people.
Luca (29:43):
Yeah, a lot to get into there, and I think that the
easiest way to think about whatwe do is is by understanding our
philosophy right, because Ithink gut health has become a
topic that everyone has heard ofat this point, for for good
reasons, for bad reasons.
You know cleanses and so on.
You know taking the next bigtrend and wherever it takes you,
(30:05):
but I think the core of what wedo is just help people realize
that gut health is health.
It's not just your abdominalpain, it's not just your bloat,
it's your mental health, it'syour immune system, it's your
digestion, of course, but it'salso your skin, it's your weight
, it's everything, and it'ssomething that everybody can
(30:26):
benefit from.
You know, whether you'resomeone dealing with an active
inflammatory condition let's sayyou have Crohn's all the way to
someone who's at the peak oftheir health you know an Olympic
athlete just looking tooptimize.
Gut health has its place acrossthat entire you know, sick,
healthy spectrum, and I thinkthe problem that a lot of us
(30:49):
face today in the modern worldis that we're very disconnected
from our bodies, which I thinkis kind of what we're discussing
here, where wearables can helpus understand some of the
underpinnings of what's going onday to day.
But on top of that, we have somany external stressors, right,
we have processed foods thathave become the norm in the diet
(31:09):
for the high majority of people.
We have antibiotic overuse,which has its own problems.
We have environmental hazards,we have chronic stress and
because of that, our bodies aremissing out on a lot of the
natural elements that they need,contributing to a lot of the
widespread health issues that wesee today, especially in
chronic health.
And on top of this, becausewe're so busy, because we're
(31:34):
always running to the next thing, we don't take that time to
check in with our bodies.
So we've been on our ownjourneys, myself and Yuli as
well.
So being able to look into thatraw data is something that is
second nature to us, but I don'tput that expectation on
everyone.
And the sad part is that theresearch is showing that all
(31:54):
these innate systems in ourbodies are not isolated.
You know, they have far, farreaching impacts on things like
our mood and our health, morethan we ever once thought.
So that disconnection betweenus and our bodies is becoming
more and more important, andsome people are definitely aware
of it.
You know, that's kind of wherethe whole, I would say,
(32:15):
biohacking revolution is comingfrom, but the sad part is that a
lot of these people don'tnecessarily have the background
to act on it properly.
So we see people focused ontaking 30 different supplements
before they're even consideringthe fundamentals of their diet,
their sleep and their stress,which I think we all know is
(32:37):
that's going to have a muchlarger impact before the
supplements.
And if you don't address thosethings first, the supplements
can't have their effect.
So understanding the place forthose things is super important.
So for us, it really all comesdown to helping you understand
what your body's trying to tellyou.
The way I like to think of whatwe do is that we're essentially
just translators.
Your body has all theinformation it's trying to tell
(32:59):
you what it needs, but we're sodisconnected that we don't know
how to speak the languageanymore.
So what we really do is helppeople focus on those seven
hours that they're typicallyspending in the bathroom on a
weekly basis and turn that intoconcrete, powerful health
insights using artificialintelligence, using microbiome
(33:21):
testing, using smart sensors,because there's around 60% of
people, especially adults, whoare struggling with gut health
issues and health issues ingeneral, and they're
experiencing symptoms butthey're not able to make the
leap of turn it into?
What do I do next so that guthealth optimization is something
that we're really focused on,so that we can make gut health
(33:44):
and health itself as natural asyour daily routine, essentially?
Yuli (33:50):
So, and the product itself is essentially a test right.
Luca (33:55):
Yeah, the product itself is a combination of three things
it's a at-home microbiome test,it's a app and it's a bathroom
sensor.
So the bathroom sensor isreally about habit formation.
Essentially, it uses Bluetoothto recognize when you go to the
bathroom with your phone.
We'll send you a reminder tocheck in with our app, and it's
(34:17):
also able to passively track howlong you're in the bathroom,
how frequently you're going,which is important to get to
know.
And in the app you can do a lotof things.
You can tell us about thesymptoms you're experiencing,
your diet, your mental health.
You can track basically all theimportant areas of your
well-being.
But on top of that, it's also atrustworthy informational
(34:38):
resource.
So we have a tool called GutChat, similar to conversational
chat that you might experiencein other apps, but the unique
thing about ours is that it'snot connected to the internet
and it's actually trained onhundreds of thousands of
peer-reviewed academicliterature.
(34:58):
So when you ask a question, youcan be very confident that the
information is coming from aplace of trust, something that's
been reviewed by otherscientists and so on, and we
always make sure to cite thatinformation so you can see the
exact resources that it's comingfrom.
On top of that, we make itreally easy for you to dig into
topics.
(35:19):
So if you ask a question aftera response, we'll give you some
follow-up questions you can ask.
You can just keep diving deeperinto topics and again get that
confidence in areas of yourhealth that either might be
uncomfortable to discuss withother people or you've just
never known what to trust,Because when you Google it you
just kind of see a slew ofinformation everywhere.
Yuli (35:39):
So education and tracking are two big things I just pause
you there because I think it's avery important topic that you
just touched on with the ai chatfeature, and I just want to
make sure that our listenersfully understood that, because
you kind of isolate this dataand you control the sources of
(36:00):
this data.
It's a very different and, justyou know, asking Chad GBT what
is this gut symptom that I'mhaving, right?
So you created your own kind ofthis trusted source that, yes,
people can converse and maybesense more privacy than sharing
it with, even with theirpractitioner, right but at the
(36:21):
same time, they also can trustthat the data and advice they
get comes from trusted sources,which I think is another big
issue.
Kind of look back to our AIconversation.
Another big issue that we'reseeing is this mistrust of data,
or data that is oftenmisleading or creating
misinformation.
So I just love that idea and Iwanted to emphasize and maybe,
(36:45):
like educate right our audienceon that.
It is one of the use cases ofAI these days and this is
something that allows you tohave that again trusted source
and valuable information thatyou know, if you asked an
average practitioner to rememberall this incredible research
(37:07):
right that you're able to storein this one kind of library of
content that would be justimpossible for an individual.
But again, with AI you're ableto access like countless of
research and have that in yourfingertips.
So I just wanted to emphasizethat, because it's funny how we
talked today about some of thosethings that are so obvious,
(37:28):
right, but like just a few yearsago, you could never imagine
doing that, right.
Luca (37:34):
No, you couldn't, and the information comes out so quickly
that even if you tried, youwouldn't be able to keep up
right.
So us being able to pull theinformation from the literature
as it's coming out and distillit into a way that you can ask
questions about very easily is ahuge, huge, huge benefit to
practitioners, not only fortheir own knowledge but also for
(37:56):
their patients, right whenthey're away from the care.
They're able to ask questions,to get responses from databases
they can trust, which is super,super important, because for us,
transparency in data is areally big item that we talk
about a lot LLMs, these chat,gpts and so on that are out
(38:16):
there.
When you ask a question, youhave no idea where it pulled
that information from, and mostof these tools are also not
connected to the internet mostof the time, but in a way that
doesn't benefit them, becausethat means a lot of their
information is outdated andbecause they have such a
widespread amount of information, including a download of the
entire internet, they don'tnecessarily know.
(38:39):
You know, is this random blogcorrect, or is it something that
is potentially giving mecompletely false information?
We don't have that problembecause all of our resources are
peer-reviewed literature.
So we're able to pull from theresources, we're able to see
papers that are saying similarthings.
Papers that have lessreproducibility can be ignored,
(39:01):
for example, and we always,always cite information.
We will show you the exactpaper that it came from so that
you can go look into it yourselfdeeper and again feel that
confidence of the informationthat's there.
So being able to one-up youreducation is something that's
super important, and then thenext layer on top of that is
(39:23):
receiving those responses,receiving those information in a
way that's easilyunderstandable, because, coming
from my science background, oneof the things that I never
understood is that why academicliterature is so difficult to
read.
It's written extremely dry,there's a lot of technical
jargon, and it makes it so thatvery few people can get value
(39:49):
from it.
And that's why so much of thegreat information and the great
resource that's happening staysin the academic sphere, because
people just don't know what it'ssaying.
And that's not.
You know, even if you're aprofessor, you go from one
department to the next.
It might be like speakinganother language.
So for us, it's not just beingable to get access to
information, but also in aformat that you can easily
(40:10):
understand, and, on top of that,with contextualization of your
individual needs.
If you ask about a specificbacteria, a specific probiotic,
specific diet, we can give you aresponse from literature about
all the information you need toknow, but also how it's
applicable to you, because wealso know about your diet, we
(40:32):
know about your symptoms.
We could say this looks like itcould be useful for you because
of what you're eating, becausethe symptoms you're experiencing
, and just become so much morerelevant as a result of that.
So personalization is anotherkey area that AI can be
supportive of.
Yuli (40:48):
Amazing.
Well, thank you for thisincredible overview and I can
believe it's been.
We're running out of time.
There's so many more questionsthat I want to ask you, but as
to kind of wrap things up forbecause I think we gave a lot of
information to people, what canpractitioners do today?
What are kind of the mostimmediate things that they can
(41:10):
start incorporate into theirpractice whether it's data, ai,
different tools just to get moreaccess to this valuable
information and enhance theirservices?
Luca (41:22):
this valuable information and enhance their services.
Yeah, I think one of the mostimportant things that people can
do is use AI as something tosupport education.
I think is a really, really bigone.
So being able to keep up todate on information.
There's several evennewsletters out there that are
constantly distilling all theinformation from different areas
(41:42):
of health, that are constantlydistilling all the information
from different areas of healththat are super relevant for
people to keep up with.
Down to just managing yourday-to-day practice right.
How do you support peoplebetter when they're not directly
in front of you?
Ai is going to be the best wayto do that.
Obviously, I'm biased.
I'm going to say my products isthe best thing to do that to
give people confidence in theirhealth outside of direct care.
(42:04):
But there are many differentoptions that go beyond simply
journaling in your phone as thebest option and certainly better
than just Googling it to seewhat information might be there.
So I think practitioners shoulddefinitely take the leap in
understanding that AI could be acomplement to their care.
I've been in this space forfive years.
I can tell you we are nowherenear replacement, nor do I think
(42:26):
it's ever possible, justbecause of the human touch, care
it requires.
And so, yeah, just making AIpart of your practice and the
way that you deliver to people.
Yuli (42:37):
And considering some of those incredible products, like
your test incorporating into it.
We're seeing a lot ofpractitioners also creating
partnerships with or just usingit on their own by recommending
some of those tests and tools totheir clients because it gives
them a lot more data, right,Certainly, certainly.
Well, thank you so much forsharing this wall of knowledge.
(42:59):
We didn't get to talk aboutyour personal story because we
ran out of time, so we mighthave to do a part two because
that sounds fascinating and somuch you've overcome to get here
and help so many other people.
So really appreciate yourmission, your journey, sharing
all of this incredible insightsfor Alyssa.
Thank you so much, Luca.
Luca (43:20):
My pleasure.
Thanks so much, Luca, mypleasure.
Thanks so much Julie.
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